Systems and methods for communicating with an electric vehicle

ABSTRACT

Methods and systems for communicating data with an electric vehicle are disclosed. According to some aspects, insurance risk related data associated with use of the electric vehicle may be collected and stored in one or more memories included in the electric vehicle. When the electric vehicle is connected to an electrical grid for charging a battery included in the electric vehicle, in some implementations, a power-line communication unit may transmit the insurance risk related data over the electrical grid to one or more remote computer systems. The insurance risk related data may be used by an insurer to calculate insurance rating data so that an insurance premium (or rate, discount, usage-based insurance, etc.) associated with the electric vehicle and/or its driver can be adjusted to more accurately reflect a risk of recognizable loss. The insurance risk data may be related to driving or driving behavior, and/or vehicle operation.

CROSS-REFERENCE TO RELATED APPLICATION

This is a continuation of U.S. Pat. Application No. 14/839,002, filedAug. 28, 2015, which is an application claiming the benefit of thefiling date of U.S. Provisional Pat. Application No. 62/069,693, filedOct. 28, 2014. The entire contents of each of the foregoing areincorporated herein by reference for all purposes.

FIELD OF DISCLOSURE

The present disclosure relates generally to vehicle communicationmethods and systems, and more particularly, to communicating insurancerisk related data with an electric vehicle.

BACKGROUND

Vehicle insurance providers typically seek to offer insurance policypremiums that take into account the likelihood of an event triggering arecognizable loss under the insurance policy (e.g., damage to thevehicle covered by the policy, damage to another vehicle or object,injury to the policy holder, injury to others, etc.). Past drivingbehavior of a policy holder may be useful in determining whether arecognizable loss will occur in the future. For example, an individualwho routinely drives his or her vehicle above the speed limit may bemore likely to incur a recognizable loss than an individual whogenerally does not exceed the speed limit. Other factors which may beuseful in determining the risk of recognizable loss include the distancethat the vehicle is driven on a daily, weekly, monthly and/or yearlybasis, the general condition of the vehicle, and/or the locations inwhich the vehicle has been driven (e.g., urban, rural, off-road, etc.).

Typically, individuals who demonstrate driving behaviors indicative of alow risk of recognizable loss may be assigned a more positive insurancerating, and accordingly, offered a lower insurance premium. On the otherhand, individuals demonstrating driving behaviors associated with a highrisk of loss may be assigned a more negative rating, and therefore,offered a higher insurance premium, for the same level of coverage.

Insurance providers typically may not have access to very muchinformation regarding the driving behavior and vehicle condition oftheir current and/or potential policy holders. Sources of suchinformation may be limited to driving records and/or responses by thecurrent and/or potential policy holder to questionnaires administered bythe insurance provider. Moreover, some driving behaviors, particularlythose that have a significant impact on the risk of recognizable loss,may be difficult, if not impossible, to assess based upon drivingrecords, questionnaires, and/or other conventional techniques forlearning driver behaviors. Consequently, insurance ratings and premiumsmay not accurately reflect the policy holder’s true risk of loss.

SUMMARY

A system and method that may communicate data with an electric vehicle(such as either a fully electric vehicle or a hybrid electric vehicle)over an electrical grid when the electric vehicle is connected to anelectrical grid for charging are provided. As a result, the electricvehicle may advantageously communicate insurance risk related data withan insurer and/or other remote entity over the electrical grid withouthaving to connect to a wireless network (e.g., a cellular network).Additionally, the insurer may advantageously collect insurance riskrelated data from the electric vehicle on a relatively regular basis(e.g., whenever the electric vehicle is connected to the electrical gridfor charging).

In one aspect, a computer-implemented method of communicating data withan electric vehicle may be provided. The method may include collectinginsurance risk related data associated with use of the electric vehicle,such as via one or more vehicle-mounted processors. Additionally, themethod may include storing, such as under the direction of the one ormore vehicle-mounted processors, the insurance risk related data in oneor more memories included in the electric vehicle. The method mayfurther include receiving an indication (such as at or via the one ormore vehicle-mounted processors) that the electric vehicle is connectedto an electrical grid for charging a battery included in the electricvehicle. Furthermore, the method may include transmitting the insurancerisk related data with or from a power-line communication unit (and/orunder the control or direction of the one or more vehicle-mountedprocessors) over the electrical grid from the electric vehicle to one ormore remote servers when the electric vehicle is connected to theelectrical grid for charging the battery. The method may includereceiving the insurance risk related data at an insurance providerremote processor, and/or generating, adjusting, or updating an insurancepolicy, premium, rate, risk, discount, or reward, and/or usage-basedinsurance, for the electric vehicle at the insurance provider remoteprocessor based upon the insurance risk related data received from theelectric vehicle to facilitate insurance product pricing that is morereflective of true or actual risk. The method may include additional,fewer, or alternate actions, including those discussed elsewhere herein.

In another aspect, a system of communicating data with an electricvehicle may be provided. The system may include one or more processorsand one or more memories connected to the one or more processors (suchas vehicle-mounted processors and memories). The one or more memoriesmay include non-transitory computer-readable instructions that, whenexecuted by the one or more processors, cause the one or more processorsto: collect insurance risk related data associated with use of theelectric vehicle; store the insurance risk related data in the one ormore memories; receive an indication that the electric vehicle isconnected to an electrical grid for charging a battery included in theelectric vehicle; and/or control a power-line communication unit totransmit the insurance risk related data over the electrical grid (fromthe electric vehicle) to one or more remote servers. The one or moreremote servers may be associated with an insurance provider, and theinsurance risk related data may be used to generate or adjust aninsurance policy (and/or premium, discount, rate, usage-based insurance,etc.) for the electric vehicle. The system may include additional,fewer, or alternate components, including those discussed elsewhereherein.

In another aspect, a tangible computer-readable medium includingnon-transitory computer-readable instructions that, when executed at oneor more processors of a communication system for an electric vehicle,cause the one or more processors to: collect insurance risk related dataassociated with use of the electric vehicle; store the insurance riskrelated data in one or more memories included in the electric vehicle;receive an indication that the electric vehicle is connected to anelectrical grid for charging a battery included in the electric vehicle;and/or transmit the insurance risk related data with a power-linecommunication unit over the electrical grid to one or more remoteservers when the electric vehicle is connected to the electrical gridfor charging the battery such as adjustments to an insurance policy forthe electric vehicle is facilitated. The computer-readable medium mayinclude instructions that direct additional, less, or alternatefunctionality, including that discussed elsewhere herein.

BRIEF DESCRIPTION OF THE DRAWINGS

There are shown in the drawings arrangements which are presentlydiscussed, it being understood, however, that the present embodimentsare not limited to the precise arrangements and instrumentalities shown,wherein:

FIG. 1 illustrates an exemplary environment associated withcommunicating insurance risk related data with an electric vehicle inaccordance with principles of the present disclosure;

FIG. 2 depicts a block diagram illustrating an exemplary computer systemon which a method of communicating insurance risk related data with anelectric vehicle may operate in accordance with principles of thepresent disclosure; and

FIG. 3 is a flow chart of an exemplary method of communicating insurancerisk related data with an electric vehicle in accordance with principlesof the present disclosure.

The Figures depict preferred embodiments of the present invention forpurposes of illustration only. One of ordinary skill in the art willreadily recognize from the following discussion that alternativeembodiments of the structures and methods illustrated herein may beemployed without departing from the principles of the inventiondescribed herein.

DETAILED DESCRIPTION

The systems and methods disclosed herein generally relate tocommunicating insurance risk related data, among other types of data,with and/or from an electric vehicle over an electrical grid by way ofpower-line (and/or wired) communication. The electric vehicle mayinclude various processors and/or sensors that collect various types ofinformation related to vehicle and/or driver risk, such as dataindicating driving or driver behavior and/or vehicle operation. Theinsurance risk related data may be transmitted from the electric vehiclevia the electrical grid to an insurance provider remote processor (orserver). The insurance provider remote processor may then use theinsurance risk related data to generate or adjust an insurance policy(and/or insurance premium, rate, discount, points or rewards program,etc.) for the electric vehicle and/or the owner or driver(s) of theelectric vehicle. As such, more accurate levels of risk, or lackthereof, may be determined for the electric vehicle and/or driversthereof, and insurance cost savings may be calculated and passed on torisk averse drivers.

More specifically, power-line communication systems may provide theability to carry data on a conductor that may be also used to distributeAC and/or DC electric power. The infrastructure necessary to supportpower-line communications has become more widespread, in part, due tothe recent interest in transforming the electrical grid into a smartgrid. Electric vehicles may be periodically plugged into the electricalgrid to charge their batteries. The systems and methods of the presentdisclosure take advantage of the recent adoption of power-linecommunication technologies, and the growing popularity of electricvehicles, to provide insurance companies, and other entities, with theability automatically to collect data from an electric vehicle when itis connected to the electrical grid for charging.

The systems and methods of the present disclosure may utilize existingonboard data collection systems that collect insurance risk related datafrom one or more sensors and/or subsystems onboard a vehicle.Additionally, or alternatively, the insurance risk related data may becollected from one or more aftermarket data collection systems and/orone or more aftermarket sensors installed in the vehicle post-productionby, for example, the purchaser of the vehicle or another individual whois not the vehicle manufacturer. The insurance risk related data mayreflect information generated by any of various devices and subsystemsof an electric vehicle, such as devices that monitor and/or controloperational parameters of the vehicle (e.g., velocity, braking,steering, acceleration, odometer information, tire pressure, engineperformance, revolutions per minute, whether a cruise control may orother automated driving system is activated, etc.), diagnostic systems(e.g., a battery charge level sensor, a motor temperature sensor, oillevel sensor, etc.), devices that sense and/or monitor characteristicsof the environment external to the vehicle (e.g., still image cameras,video cameras, lidar, radar, etc.), devices that monitor the driverand/or passengers inside the cabin of the vehicle (e.g., still imagecameras, video cameras, microphones, seat occupant sensors, temperaturesensors, etc.), and/or navigational devices (e.g., dedicated onboardglobal position systems, mobile phones with applications that locate themobile phone using GPS or cell tower triangulation, etc.), etc. In oneembodiment, the onboard data collection system may be similar to thatdescribed in U.S. Pat. Application No. 14/057,419, the entirety of whichis hereby incorporated by reference.

By transmitting the data collected by these onboard sensors and/orsystems to an insurance provider, the systems and methods of the presentdisclosure may help the insurance provider more accurately predict thelikelihood of a policy holder causing and/or suffering damage with hisor her vehicle. This knowledge may enable the insurance provide toassign an insurance rating to the policy holder that better approximatesthe risk of recognizable loss and/or adjust an insurance premium to moreaccurately reflect the risk of recognizable loss.

Furthermore, the systems and methods of the present disclosure may freethe policy holder from having to transmit the insurance risk relateddata via his or her mobile phone and/or installing a wirelesscommunication unit in his or her vehicle for wirelessly transmitting theinsurance risk related data. Additionally, since an electric vehicle maybe connected to the electrical grid for charging on a fairly regularbasis (e.g., daily, weekly, monthly, etc.), an insurance provider may beable to collect relatively up-to-date insurance risk related data on thepolicy holder. Also, the systems and methods of the present disclosuremay be automated so that the collection of the insurance risk relateddata may occur without any substantive action by the policy holder.

I. Conventional Technologies

Wireless communication technologies have made it feasible to remotelyaccess sensor data collected by an onboard computer of a vehicle.However, such systems typically may require the use of a mobile phone towirelessly transmit the data to the insurance provider and/or theinstallation of a wireless communication unit in the vehicle. Also,depending upon the location of the vehicle, it may be difficult toestablish a wireless connection with the vehicle (e.g., when the vehicleis parked in an underground parking garage where the available wirelesssignal may be weak). Additionally, configuring the vehicle to haveinternet access may require the owner to purchase a relatively expensivedata plan from a wireless (e.g., cellular) provider for the vehicle.Thus, while obtaining data from the onboard computer of the vehiclethrough wireless communications may be possible, it may sometimes not bea very economic and/or a reliable option for collecting suchinformation.

One method for wirelessly transmitting the onboard computer data may beto physically and/or wirelessly connect a mobile phone to the onboarddiagnostics communication port so that the mobile phone may retrieve thesensor data saved on the onboard computer and/or then wirelesslytransmit the data to the insurance provider. However, many electricvehicles (e.g., a battery electric vehicle, a plug-in hybrid electricvehicle, an extended-range electric vehicle, etc.) lack an easilyaccessible onboard diagnostics communication port. This may be becauseonboard diagnostics communication ports are generally included foremissions testing purposes, and electric vehicles typically may not besubjected to such testing. Accordingly, collecting sensor data from theonboard computer of an electric vehicle may not be as straightforward ascollecting such data from a conventional internal combustion enginevehicle. The present embodiments may alleviate these and/or otherdeficiencies.

II. Exemplary Environment for Communicating With An Electric Vehicle

FIG. 1 depicts an exemplary environment 10 associated with communicatinginsurance risk related data with, and/or from, an electric vehicle.Although FIG. 1 depicts certain components and systems, it will beappreciated that additional or alternate components and systems areenvisioned.

As illustrated in FIG. 1 , the environment 10 may include a powerstation 11 that supplies electricity to various consumers via anelectrical grid 12. The consumers may include residential buildings suchas homes 14 a, 14 b, 14 c, businesses such as an insurance provider 16,vehicles such as an electric vehicle 20, and/or other electricityconsuming devices, systems, and entities.

The power station 11 may generate electricity by using a generator toconvert mechanical or chemical energy into electrical energy. The powerstation 11 may be a thermal power station that harnesses energy fromfossil fuels such as coal and natural gas, radioactive materials, wasteheat from industrial processes, etc. Alternatively, the power station 11may harness energy from renewable sources such as hydropower, solar,wind, geothermal, biomass, etc. Several different types of powerstations may supply electricity to the electrical grid 12.

The electrical grid 12 may be an interconnected network for transmittingelectricity from the power station 11 to the consumers. The electricalgrid 12 may include multiple power lines 22 for transmitting theelectricity over long distances. The power lines 22 may be made of aconductive material such as copper. Some of the power lines 22 may below-voltage distribution lines that deliver electricity directly toindividual consumers, and some of the power lines 22 may be high-voltagetransmission lines that carry electricity over long distances.

The electrical grid 12 may include one or more step-up transformers 30which increase the voltage of the electricity produced by the powerstation 11 so that the electricity can be transmitted over longdistances with minimal resistance power losses. The electrical grid 12may also include step-down transformers 34 which may reduce the voltageof the electricity after a long-distance transmission so that theelectricity is suitable for use by the consumer. Additionally, theelectrical grid 12 may include transmission towers 32 which may hold thepower lines 22 above the ground. The power lines 22 may also be buriedunderground.

The electric vehicle 20 may be any vehicle that is propelled by one ormore electric motors which use electricity stored in a battery oranother electrical storage device. The electric vehicle 20 may be abattery electric vehicle, plug-in hybrid electric vehicle, hybridelectric vehicle, extended-range electric vehicle, rail-borne electricvehicle, etc. Furthermore, the electric vehicle 20 may be configured foruse as a car, crossover vehicle, sports utility vehicle, truck, train,boat, submarine, construction vehicle, heavy-equipment-type vehicles,motorcycle, scooter, bicycle, self-balancing two wheel vehicle, plane,helicopter, drone, etc.

The electric vehicle 20 may be connected to the electrical grid 12 via acharging device 40 installed near the home 14 a. The charging device 40may shorten the time necessary to charge the battery of the electricvehicle 20 as compared to connecting the electric vehicle 20 directly tothe electrical grid 12.

III. Exemplary Data Collection and Communication System

FIG. 2 is a block diagram of an exemplary system for collecting andprocessing data obtained from the electric vehicle 20 for variousinsurance-related purposes and/or other purposes. The electric vehicle20 may include a battery 110 and/or other electrical storage apparatusthat stores electricity, and, during operation, supplies electricity toone or more electric motors 112 that rotate wheels 114 of the electricvehicle 20. Various onboard sensors and/or sub-systems may be arrangedwithin and/or on the exterior of the electric vehicle 20 for collectinginsurance risk related data associated with use of the vehicle. When theelectric vehicle 20 is connected to the electrical grid 12 for chargingthe battery 20, the electric vehicle 20 may communicate the collectedinsurance risk related data via a power-line communication protocol overthe electrical grid 12 to the insurer 16. In one aspect, the insurancerisk related data may be analyzed prior to transmission to the insurer16, and in another aspect, un-processed insurance risk related data maybe transmitted to the insurer 16 for analysis.

The electric vehicle 20 may include a power supply inlet 116 removablyconnectable to an electrical plug 118 for charging the battery 110 withelectricity from the electrical grid 12. AC voltage received from theelectrical plug 118 may be converted into DC voltage by an AC to DCconverter 120 located inside the electric vehicle 20. The AC to DCconverter 120 may output DC voltage to the battery 110 for storage. Theelectric vehicle 20 may include additional, fewer, or alternatecomponents than those shown in FIG. 2 , including those discussedelsewhere herein.

A. Exemplary Data Collection Systems

The electric vehicle 20 may include hardware, firmware, and/or softwaresubsystems that monitor and/or control various operational parameters ofthe electric vehicle 20. In the electric vehicle 20 of FIG. 2 , abraking subsystem 122 may generate data indicative of how the brakes ofthe electric vehicle 20 are applied (e.g., an absolute and/or relativemeasure of applied braking force, and/or a binary indicator of whetherthe brakes are being applied, etc.), a velocity subsystem 124 that maygenerate data indicative of how fast the electric vehicle 20 is beingdriven (e.g., corresponding to a velocity, odometer reading, and/or adriver input such as depression of a gas pedal, etc.), a steeringsubsystem 126 that may generate data indicative of how the electricvehicle 20 is being steered (e.g., based upon the driver’s manipulationof a steering wheel, and/or based upon automated steering control data,etc.), and/or a diagnostics subsystem 128 that may generate other datapertaining to the operation and/or condition of the electric vehicle 20(e.g., battery charge information, electric motor temperatureinformation, engine oil level information, warning information toindicate dangerous and/or improper operation, and/or error codes toindicate software and/or hardware malfunctions within vehicle 20 such asairbag malfunctions, etc.).

The electric vehicle 20 may also include a GPS subsystem 130 thatgenerates geographic location information (e.g., data indicative of acurrent location of the electric vehicle). In one aspect, the GPSsubsystem 130 may employ positioning techniques different from GPS, suchas cell tower triangulation, for example, for generating the geographiclocation information.

In one aspect, the braking subsystem 122, velocity subsystem 124,steering subsystem 126, diagnostics subsystem 128, and/or a differentsubsystem not shown in FIG. 2 also may generate data indicating whetherone or more automated driving systems are currently activated for theelectric vehicle 20. For example, the velocity subsystem 124 maygenerate data indicating whether a cruise control system is currentlyactivated, and, for example, the braking subsystem 122 and/or thesteering subsystem 126 may generate data indicating whether assistedsteering and/or assisted braking systems are currently activated. Inother examples, one of the subsystems 122, 124, 126, 128 and/or acombination of the subsystems 122, 124, 126, 128 may generate dataindicating whether the electric vehicle 20 is in an automatedtransmission mode or a manual transmission mode, and/or whether thedriving of the electric vehicle 20 is currently subject to completeautomated/machine control rather than manual (human) control, etc.

In yet another example, one of the subsystems 122, 124, 126, 128 and/ora combination of the subsystems 122, 124, 126, 128 may generate dataindicative of motion of the electric vehicle 20 relative to all sixdegrees of freedom (i.e., forward/backward, up/down, left/right, pitch,yaw, and roll). For example, the generated data may indicatetranslational and/or rotational G-forces (e.g., using accelerometers),which may be used to deduce directional velocity and/or accelerationwith respect to each degree of freedom.

In still further examples, one of the subsystems 122, 124, 126, 128and/or a combination of the subsystems 122, 124, 126, 128 may generatedata indicative of odometer information, steering information, driverbehavior information, velocity information, braking information, engineperformance information, and/or vehicle maintenance information (e.g.,oil change information, air filter replacement information, etc.).

The electric vehicle 20 may also include at least one external sensor132. The external sensor 132 may be a device configured to monitorcharacteristic(s) of the environment external to the vehicle 20, such asa still image and/or video camera device, a lidar (laser remote sensing)device, a radar device, and/or a sonar device, etc. The external sensor132 may be located on or inside the electric vehicle 20.

For example, the external sensor 132 may be permanently affixed to theelectric vehicle 20 (e.g., on the exterior and/or interior of the frame,on the dashboard, on the inner or outer surface of a windshield, etc.),or may be temporarily affixed to, or simply placed on or in, someportion of the electric vehicle 20 (e.g., placed on top of thedashboard, or in a device holder affixed to the windshield, etc.). Theexternal sensor 132 may be included in a portable computing device(e.g., as a software application and/or associated hardware of a mobilephone or other portable computer device), and/or may be a dedicatedsensor device.

In the electric vehicle 20 shown in FIG. 2 , the external sensor 132 maybe located on or inside the electric vehicle 20 such that it senses theenvironment in front of, behind, to the side, and/or above the electricvehicle 20. In one aspect, the external sensor 132 may be used incombination with other external sensors to provide a 360 degree sensingrange. In other embodiments, however, the external sensor 132 may beomitted.

In one aspect, the external sensor 132 and/or other external sensors maygenerate data indicative of proximity information (e.g., the distance bywhich the electric vehicle 20 follows another vehicle), driftinginformation (e.g., how often the electric vehicle 20 drifts from itslane), lane changing information (e.g., how frequent the electricvehicle 20 changes lanes), weather information (e.g., whether theelectric vehicle 20 is driven in rain, sleet, snow, high windconditions, low temperatures, high temperatures, etc.). In one aspect,the external sensor 132 and/or other external sensors may generate dataindicative of an amount of time the vehicle 20 has been exposed to coldtemperatures (e.g., below 0° C.), so that such data may be used tocalculate the impact of cold temperatures on the charge level of thebattery of the vehicle 20 and/or the condition of other components ofthe vehicle 20. In one aspect, the battery charge determined to havebeen lost to cold temperatures may be communicated to the driver throughthe dashboard or the driver’s smartphone, and/or communicated to a thirdparty via the power-line communication system disclosed herein.

The electric vehicle 20 may further include at least one cabin sensor134. The cabin sensor 134 may be a device configured to monitor aspectsof the cabin of the electric vehicle 20 and/or the occupants inside thecabin of the vehicle 20. The cabin sensor 134 may be any one of, forexample, a still image camera, video camera, microphone, seat occupantsensor, temperature sensor, etc.

The cabin sensor 134 may be permanently affixed inside the cabin of thevehicle 20 (e.g., on the dashboard, on the inner side of a windshield,inside one of the seats, etc.), or may be temporarily affixed to, orsimply placed on or in, some portion of the interior of electric vehicle20 (e.g., placed on top of the dashboard, arranged in a device holderaffixed to the windshield, etc.).

The cabin sensor 134 may track eye movement of the driver to determineif the driver is distracted, sleeping, and/or not looking at the road.The cabin sensor 134 may be included in a portable computing device(e.g., as a software application and associated hardware of a mobilephone and/or other portable computer device), and/or may be a dedicatedsensor device.

In one aspect, the cabin sensor 134 may be used in combination withother cabin sensors. In other embodiments, however, the cabin sensor 134may be omitted. In one aspect, the cabin sensor 134 and/or other cabinsensors may generate data indicative of driver behavior information(e.g., whether the driver is distracted, sleeping, not looking at theroad, etc.) and/or passenger information (e.g., number of passengers,passenger weight, passenger age, passenger behavior, etc.).

Each of the subsystems 122, 124, 126, 128, 130, the external sensor 132,and the cabin sensor 134 may generate data and/or analog informationthat may be indicative of the sensed environment. For example, where theexternal sensor 132 is a digital video camera device, the externalsensor 132 may generate data corresponding to frames of captured digitalvideo. As another example, where the external sensor 132 is an analogcamera device, the external sensor 132 may generate analog signalscorresponding to frames of captured analog video. As yet anotherexample, where the external sensor 132 is a digital lidar device, theexternal sensor 132 may generate data corresponding to frames ofcaptured digital lidar information.

In one aspect where the external sensor 132 is a digital video cameradevice, for example, the external sensor 132 may generate datacorresponding to frames of captured digital video. As another example,where the external sensor 132 is an analog camera device, externalsensor 30 may generate analog signals corresponding to frames ofcaptured analog video. As yet another example, where the external sensor132 is a digital lidar device, the external sensor 132 may generate datacorresponding to frames of captured digital lidar information

In one aspect, the electric vehicle 20 may not include one or more ofthe subsystems 122, 124, 126, 128, 130, the external sensor 132, and thecabin sensor 134, and/or the vehicle 20 may include additional sensorsor subsystems not depicted in FIG. 2 . Moreover, one or more of thesubsystems and/or sensors may be included in a portable externalcomputing device such as a mobile phone. For example, the GPS subsystem130 may include a software application running on a mobile phone thatincludes appropriate hardware for executing the application (e.g., anantenna and/or a receiver).

The electric vehicle 20 may also include a vehicle control unit 149including at least one processor 150 configured to receive data analogsignals from the subsystems 122, 124, 126, 128, 130, the external sensor132, and/or the cabin sensor 134 and/or other subsystems and/or sensors.The processor 150 may collect the data and/or analog signalssubstantially in real time, and/or in any of various different ways.

In one aspect, for example, the processor 150 may periodically sampledata and/or analog signals from the subsystems 122, 124, 126, 128, 130,the external sensor 132, and/or the cabin sensor 134, and/or may benotified by the respective subsystems and/or sensors when new data isavailable, etc. In another aspect, the processor 150 may be used incombination with other data processors and/or controllers.

In one aspect, the processor 150 may receive data from one or more ofthe subsystems 122, 124, 126, 128, 130, the external sensor 132, and/orthe cabin sensor 134 via a system bus such as a controller area network(CAN) bus. In other embodiments, the processor 150 may receive data fromone or more of the subsystems 122, 124, 126, 128, 130, the externalsensor 132, and/or the cabin sensor 134 via a wireless link, such as aBluetooth link. In another aspect, the processor 150 may collect datausing a mix of interface and/or bus types (e.g., a Bluetooth interfaceto receive data from the external sensor 132 and the cabin sensor 134,and a CAN bus to receive data from the subsystems 122, 124, 126, 128,130).

In one aspect, where one or more of the subsystems 122, 124, 126, 128,130, the external sensor 132, and/or the cabin sensor 134 generatesanalog signals, either the respective sensors/subsystems and/or theprocessor 150 may convert the analog information to a digital format.Moreover, the processor 150 may convert data received from one or moreof the subsystems 122, 124, 126, 128, 130, the external sensor 132,and/or the cabin sensor 134, to different digital formats or protocols.

After collecting and/or converting the data collected from the varioussensors and/or subsystems, the processor 150 may store the data in amemory 152 as sensor data 154. In one aspect, the sensor data 154 may bestored together with a time stamp indicating the time and/or date ofcollection of the sensor data 154. The memory 152 may be any suitabletype of data storage, such as a random access memory (RAM), a flashmemory, a hard drive memory, or any other tangible, nontransitorycomputer-readable medium. In one aspect, the memory 152 may be used incombination with other memories.

In one aspect, the processor 150 also, or instead, may collectinformation directly by detecting a manual input by an operator of theelectric vehicle 20. For example, the processor 150 may directly detectwhen a human driver has performed a particular operation, such asapplying the brakes, turning the steering wheel, pressing a button ortoggling a switch to turn on a fully automated/machine driving mode, asemiautomatic driving mode, etc. In such embodiments, the mechanismsand/or circuits that allow detection of the manual inputs may be viewedas portions of one or more of the subsystems 122, 124, 126, 128, and/or130. For example, a physical button and/or switch having a state thatindicates whether an operator has turned on a conventional cruisecontrol system may be viewed as a part of the velocity subsystem 124.

References below to data, signals, or other information provided by thesubsystems 122, 124, 126, 128, and/or 130 may encompass, in one aspect,direct indicators of operations performed manually by a human driver.Similarly, in scenarios where operation of the electric vehicle 20 isfully or partially machine-controlled, references below to informationprovided by the subsystems 122, 124, 126, 128, and 130 may encompassdirect indicators of operations performed automatically by the processor150.

After storing the data from the various sensors and/or subsystems in thememory 152, the processor 150 may execute a risk determination module156 stored in the memory 152 to analyze the sensor data 154, and storeresults relating to that analysis in the memory 152 as risk data 158.The risk determination module 156 may include a set of instructionsstored in the memory 152 to perform the following functions.

In one aspect, execution of the risk determination module 156 causes theprocessor 150 to determine if the driver exhibits aggressive drivingbehaviors by analyzing the acceleration, braking, and/or number of timesthe vehicle exceeded the speed limit, etc. In one aspect, execution ofthe risk determination module 156 may cause the processor 150 toidentify an accident by processing data from velocity subsystem 124 toidentify a very sudden change in velocity of electric vehicle 20, and/orby implementing image/video processing of the data from the externalsensor 132 to identify a collision with another vehicle and/or object,etc.

In one aspect, the processor 150 may execute the risk determinationmodule 156 to analyze data from the various sensors and/or subsystemssubstantially in real-time (e.g., as the data is collected by theprocessor 150) in order to generate risk indicators reflecting the levelof risk associated with the environment in which the electric vehicle 20is driven, the operation of the electric vehicle 20, the condition ofthe electric vehicle 20, and/or the behavior of the driver and/orpassengers of the electric vehicle 20.

Examples of ways in which the risk indicators may be determined, and ofthe types of correlation models and/or data that may be used todetermine the risk indicators, are discussed below in connection withthe computer system of the insurer 16. Once each risk indicator isgenerated for a particular time period, the risk indicator may be storedin the memory 152 as part of the risk data 158, and the sensor data 152in memory 152 that corresponds to that same time period may be erased tomake room for new sensor data. In this manner, the storage requirementsof the memory 152 may be reduced, which may be useful in view of thelarge volume of data that may be generated by one or more of thesubsystems 122, 124, 126, 128, 130, the external sensor 132, the cabinsensor 134, and/or other vehicle sensors and subsystems.

The electric vehicle 20 may include a user interface 159 having adisplay 160 and/or an input device 162. The user interface 159 may beaffixed to the inside of the cabin of the electric vehicle 20, forexample, on the dashboard, or may be configured as part of a portablecomputer such as a mobile phone. In one aspect, the display 160 may beused to display the results of the risk determination module 156 to thedriver of the electric vehicle 20. In another aspect, the display 160may display information transmitted from the insurer 16 to the electricvehicle 20 over the electrical grid 12. The input device 162 may be usedby the driver to input information for storage in the memory 152 and/orfor inputting instructions for controlling the various sensors and/orsubsystems. In one aspect, the display 160 and the input device 162 maybe combined in the form of a touch screen.

B. Exemplary Communication Systems

When the electric vehicle 20 is connected to the electrical grid 12 forcharging the battery 110, a power-line communication unit 170 includedin the electric vehicle 20 may obtain the sensor data 154, the risk data158, and/or other insurance risk related data stored in the memory 152and transmit it over the electrical grid 12 to the insurer 16 and/oranother remote entity. The power-line communication unit 170 may operateby adding a modulated carrier signal (e.g., a radio frequency signal) toan AC power line 171 extending between the power supply inlet 116 andthe AC to DC converter 20 of the electric vehicle 20.

The modulated carrier signal may include information representing thesensor data 154, the risk data 158, and/or other insurance risk relateddata stored in the memory 152. The modulated carrier signal may betransmitted together with the AC voltage over the electrical grid 12 todistant locations, such as the insurer 16. In one aspect, the power-linecommunication unit 170 may be configured as a Broadband Over Power Line(BPL) modem that transmits modulated carrier signals having a frequencyin the range of approximately (e.g., ± 10%) 1 to 100 MHz, or 1.6 to 80MHz, or 10 to 80 MHz, or 20 to 60 MHz, or lesser or greater.

The processor 150 may execute a power-line communication module 172stored on the memory 152 for controlling the transmission of data by thepower-line communication unit 170. As described below in more detail,executing the power-line communication module 172 may involve theprocessor 150 identifying that the power supply inlet 116 is connectedto the electrical plug 118, for example, when the battery 110 is beingcharged.

In one aspect, the processor 150 may receive a signal from the battery110 indicating that the battery 110 is being supplied with electricity.In another aspect, the processor 150 may receive a signal, via thepower-line communication unit 170, from the insurer 16 requestingtransmission of the sensor data 154, the risk data 158, and/or otherinsurance risk related data stored in the memory 152.

In another aspect, the insurer 16 may be notified by an electric utilitycompany that the electric vehicle 20 is connected to the electrical grid12 for charging, and the insurer 16 may subsequently transmit a signalto the electric vehicle 20 requesting transmission of the sensor data154, the risk data 158, and/or other insurance risk related data storedin the memory 152. The reception of the battery charging signal and/orthe data request signal from the insurer 16 may cause the processor 150to transmit the sensor data 154, the risk data 158, and/or otherinsurance risk related data stored in the memory 152 to the power-linecommunication unit 170, or cause the power-line communication unit 170to directly retrieve the sensor data 154, the risk data 158, and/orother insurance risk related data from the memory 152. Once inpossession of the sensor data 154, the risk data 158, and/or otherinsurance risk related data, the power-line communication unit 170 mayconvert the data into a modulated carrier signal (e.g., a radiofrequency signal) that may be transmitted over the electrical grid 12 tothe insurer 16.

In one aspect, the charging device 40 may include a switch 180, acharging control portion 182, and a power-line communication unit 184.The charging control portion 182 may selectively control the switch 180to connect the electrical plug 118 to the electrical grid 12 and/ordisconnect the electrical plug 118 from the electrical grid 12. Inanother aspect, the power-line communication unit 184 may receive asignal from an electric utility company indicating that the chargingcontrol portion 182 should disconnect the electrical plug 118 from theelectrical grid 12 due to, for example, excessive demand on theelectrical grid 12 from consumers. Additionally, the power-linecommunication unit 184 may receive a signal from the electric utilitycompany indicating that the charging control portion 182 should connectthe electrical plug 118 to the electrical grid 12 to charge the battery110 due to low demand on the electrical grid 12 (e.g., during theevening).

In one aspect, the insurer 16 may possess a power-line communicationunit 190 connected to the electrical grid 12 for receiving the sensordata 154, the risk data 158, and/or other insurance risk related datastored that is transmitted from the power-line communication unit 170 ofthe electric vehicle 20. As discussed below in more detail, the insurer16 may have a data analysis unit 192 for analyzing the sensor data 154,the risk data 158, and/or other insurance risk related data transmittedfrom the electric vehicle 20 to determine risk indicators and/or aninsurance rating for the driver of the electric vehicle 20 based uponthe operation and/or condition of the electric vehicle 20, the behaviorof the driver and/or passengers, and/or the environment in which theelectric vehicle 20 is operated. The insurer 16 may transmit the riskindicators, the insurance ratings, and/or other data (e.g.,advertisements) via the power-line communication unit 190 over theelectrical grid 12 to the power-line communication unit 170 of theelectric vehicle 20, so that such information may be displayed on thedisplay 160 of the user interface 159 to the driver and/or otheroccupants of the electric vehicle 20.

IV. Exemplary Insurance Rating Determination System

In one aspect, the data analysis unit 192 of the insurer 16 may becapable of performing various functions, including analyzing the sensordata 154, the risk data 158, and/or other insurance risk related datareceived from the electric vehicle 20 over the electrical grid 12. Thedata analysis unit 192 may be distributed across one or more computersystems (e.g., servers) which are remote from the electric vehicle 20and which may be owned and/or operated by the insurer 16 and/or otherentities.

The power-line communication unit 190 of the insurer 16 may beconfigured to receive the sensor data 154, the risk data 158, and/orother insurance risk related data transmitted from the electric vehicle20 over the electrical grid 12, and/or store the received data in amemory 194 as collected vehicle data 196. The power-line communicationunit 190 may be configured in a similar manner as the power linecommunication unit 170 discussed above including being configured as BPLmodem. The memory 194 may be any suitable type of data storage, such asa RAM, a flash memory, a hard drive memory, or any other tangible,nontransitory computer-readable medium. The memory 194 may be part ofthe data analysis unit 194, as illustrated in FIG. 2 , or configuredseparately from the data analysis unit 194. In one aspect, the memory194 may be used in combination with other memories. The data analysisunit 192 may include at least one processor 198 which is configured toprocess the collected vehicle data 196 for various purposes as discussedbelow in more detail.

The data analysis unit 192 may include a risk determination module 200and/or additional modules not illustrated in FIG. 2 . The riskdetermination module 200 may include a set of instructions stored in thememory 194 and capable of being executed by the processor 198.

In one aspect, the data analysis unit 192 may include a driveridentification module that, when executed by the processor 198, analyzesthe collected vehicle data 196 to determine the identity of the driverof the vehicle 20. If the identity of the driver was previously embeddedin the collected vehicle data 196 by the vehicle 20 (e.g., based oninformation collected by the vehicle 20 from a key fob used by thedriver), the driver identification module may pull the identityinformation directly from the collected vehicle data 196. If theidentity of the driver was not previously embedded in the collectedvehicle data 196, the driver identification module may be executed tocompare the collected vehicle data 196 with historical data indicatingthe past driving behavior of a plurality of drivers. Based upon thehistorical data that most closely resembles the collected vehicle data196, the driver identification module may determine the identity of thedriver of the vehicle 22 that is associated with the collected vehicledata 196.

In one aspect, the processor 198 may execute the risk determinationmodule 200 to generate risk indicators based upon the collected vehicledata 196. For example, the risk determination module 200 may generaterisk indicators in an embodiment (not illustrated) where the riskdetermination module 156 of the electric vehicle 20 is omitted.Alternatively, where the electric vehicle 20 generates risk indicatorswith the risk determination module 156, the risk determination module200 may not determine risk indicators. In one aspect, where the riskdetermination module 156 of the electric vehicle 20 determines riskindicators, the risk determination module 200 may further process therisk indicators in order to generate other indicia of risk (e.g., togenerate monthly risk indicators based upon per-minute or per-day riskindicators that are provided by the electric vehicle 20).

Risk indicators may be determined using predictive modeling, which mayuse the collected vehicle data 196, as well as, correlation data 202stored by the insurer 16. The correlation data 202 may be accessed bythe risk determination module 200 and/or other modules within the dataanalysis unit 192.

In one aspect, similar correlation data may be stored, or stored inpart, by the memory 152 of the electric vehicle 20. The correlation data202 may be generated based upon historical data associated with theelectric vehicle 20 and/or other vehicles. In another aspect, thecorrelation data 202 may include data modeling correlations between: (a)patterns relating to vehicle operation as represented by sensors and/orvehicle subsystems monitoring vehicle operation, patterns relating toexternal conditions sensed by external vehicle sensors, patterns relatedto conditions inside the vehicle as sensed by cabin sensors, and/orpatterns related to diagnostic data of the vehicle; and (b) likelihoodsof incurring recognizable losses under a vehicle insurance policy. Thecorrelation data/models stored in the correlation data 202 may be basedupon manually entered information and/or may be learned by the insurer16 (and/or other computer system(s) not depicted in FIG. 2 ) based uponoperation and/or claims data of other vehicles.

The risk determination module 200 may be configured to analyze thecollected vehicle data 196 using the correlation data 202 to determineone or more risk indicators. As an example in which a relatively simplecorrelation model is used, the risk determination module 200, whenexecuted by the processor 198, may compare the percentage of time,within a predetermined time period, that the electric vehicle 20 wasoperated in a fully automated/machine driving mode (e.g., as determinedbased upon data generated by one or more of the subsystems 122, 124,126, 128, and 130) with one or more percentage ranges identified by thecorrelation data (e.g., 0-10 percent, 11-25 percent, etc.), and/ordetermine, for that time period, the risk indicator that corresponds tothe matching percentage range. The correlation data 202 may include arelational database, for example, with each percentage rangecorresponding to a different indicator of a likelihood of loss.

As another example utilizing a slightly more complex correlation model,the risk determination module 200 may process data from the velocitysubsystem 124 and data from the external sensor 132 to determine theaverage velocity of the electric vehicle 20, and/or the averagefollowing distance between the electric vehicle 20 and vehicles on theroad ahead of the electric vehicle 20, over a particular time period.Once the average velocity and the average following distance aredetermined, the risk determination module 200 may compare thosequantities with velocity/following distance models represented by thecorrelation data 202, and/or identify, for that time period, a riskindicator that corresponds to the average velocity/following distance ofthe electric vehicle 20.

More generally, the risk determination module 200 may process datacollected by one or more of the subsystems 122, 124, 126, 128, 130, theexternal sensor 132, and the cabin sensor 134, and/or other vehiclesensors and subsystems to determine when the electric vehicle 20 crossedlane markers, was not operated in conformance with traffic lights ortraffic signs, was driven at erratic velocities, was driven withexcessive braking, and/or was otherwise driven in any other manner thathas previously been determined (e.g., by the insurer 16) to correspondto a higher (or lower) risk of accident/loss, or to determine when theelectric vehicle 20 was driven in low-visibility conditions (e.g., rainyor snowy weather), in a high-traffic environment (e.g., an urban area),on streets in disrepair (e.g., bumpy, full of pot holes, etc.), and/orin any other conditions external to the electric vehicle 20 that havepreviously been determined to correspond to a higher (or lower) risk ofaccident/loss.

Each risk indicator may include a single value or code, or a pluralityof risk indices. In one aspect, for example, a monthly risk indicatormay include risk indices that are generated each hour (or each hour whenthe electric vehicle 20 is operated, etc.), and a monthly rating andpremium are determined based upon all of the hourly risk indicesgenerated for their respective month. The hourly risk indices may beweighted (e.g., according to the amount of time that the electricvehicle 20 was driven during that hour), or raw risk indices may be usedto determine the insurance rating and/or insurance premium. In asituation where the electric vehicle 20 is driven by an individual notyet insured by the insurer 16, the risk indicators may be used todetermine an insurance rating and corresponding insurance premium to beoffered to the individual.

Once the risk indicators are determined by the risk determination module200 and/or the risk determination module 156, the risk indicators may beprovided to an insurance rating module 204, which may be part of thedata analysis unit 194 and/or another computer system, and which mayinclude a set of instructions capable of causing the processor 198 todetermine an insurance rating for a driver of the electric vehicle 20based upon the risk indicators. For example, in an embodiment where therisk determination module 200 and/or the risk determination module 156generates periodic (e.g., weekly, monthly, etc.) risk indicators, theinsurance rating module 204 may determine an insurance ratingcorresponding to one or more of the risk indicators (e.g., a monthlyinsurance rating corresponding to a monthly risk indicator, a monthlyinsurance rating corresponding to a set of tens or hundreds of hourlyrisk indicators, an annual insurance rating corresponding to a set ofweekly risk indicators, etc.).

The insurance ratings may in turn be provided to a billing unit (notshown) that is configured to determine premiums for an insurance policyof the driver of the electric vehicle 20, and/or an insurance policyassociated with the electric vehicle 20 itself, based upon the insuranceratings (or, alternatively, based directly on the risk indicators). Inone aspect, where the risk determination module 200 and/or the riskdetermination module 156 generates monthly risk indicators, and wherethe insurance rating module 204 determines corresponding monthlyinsurance ratings, the billing unit may determine a monthly insurancepremium corresponding to each monthly insurance rating.

In one aspect, after determining the insurance rating and/or insurancepremium, the insurer 16 may transmit data indicative of the insurancerating and/or insurance premium via the power line communication unit190 over the electrical grid 12 to the power-line communication unit 170of the electric vehicle 20. The electric vehicle 20 may store this datain its memory 152 and/or display this data to the driver of the electricvehicle 20 via the display 160 of the user interface 159.

V. Exemplary Method of Communicating Data With An Electric Vehicle

FIG. 3 is a flow diagram of an exemplary method 300 of communicatinginsurance risk related data with, and/or from, an electric vehicle. Inone aspect, the method 300 may be implemented, in whole or in part, onone or more devices or systems such as the electric vehicle 20 of FIGS.1 and 2 . Alternatively, or additionally, in one aspect, the method 300may be implemented, in whole or in part, by the charging device 40and/or the insurer 16 of FIGS. 1 and 2 . For instance, the method may beimplemented — either alone or in combination — by the electric vehicle20, charging device 40, and/or an insurance provider remote processor orserver. In one aspect, the method may be saved as a set of instructions,routines, programs, and/or modules on a memory such as the memory 152and/or the memory 194 shown in FIG. 2 .

The method 300 may begin with collecting insurance risk related dataand/or other data from one or more of the subsystems 122, 124, 126, 128,130, the external sensor 132, the cabin sensor 134, and/or other vehiclesensors and subsystems (block 305). In one aspect, the vehicle controlunit 149 may collect the insurance risk related data during operation ofthe electric vehicle 20 (e.g., while the electric vehicle is beingdriven) and/or after the electric vehicle 20 has been stopped and turnedOFF. The processor 150 may execute a data collection module stored inthe memory 152 of the vehicle control unit 149 to collect the insurancerisk related data.

The insurance risk related data may include any one of, or anycombination of, odometer information, steering information, accelerationinformation, braking information, velocity information, engineperformance information, vehicle maintenance information, proximityinformation, drifting information, lane changing information, weatherinformation, driver behavior information, passenger information,geographic location information, and/or any other type of informationassociated with use of the electric vehicle 20. The insurance riskrelated data may also include any one of, or any combination of, thetypes of information discussed above in connection with the subsystems122, 124, 126, 128, 130, the external sensor 132, and/or the cabinsensor 134.

After collecting the insurance risk related data, the insurance riskrelated data may be stored in one or more memories included in theelectric vehicle 20, such as the memory 152 (block 310). The sensor data154 stored in the memory 152 may be formed, in whole or in part, by theinsurance risk related data collected from one or more of the subsystems122, 124, 126, 128, 130, the external sensor 132, the cabin sensor 134,and/or other vehicle sensors and subsystems.

In one aspect, where one or more of the subsystems 122, 124, 126, 128,130, the external sensor 132, and/or the cabin sensor 134 may generateanalog signals, the method 300 may involve converting the analoginformation to a digital format with the respective sensors/subsystemsand/or with the processor 150 of the vehicle control unit 149. Moreover,the processor 150 may convert the insurance risk related data receivedfrom one or more of the subsystems 122, 124, 126, 128, 130, the externalsensor 132, and/or the cabin sensor 134, to different digital formats orprotocols prior to storing the insurance risk related data in the memory152.

After storing the insurance risk related data, the processor 150 mayexecute the risk determination module 156 stored in the memory 152 toanalyze the sensor data 154, and store results relating to that analysisin the memory 152 as part of the risk data 158 (block 315). As discussedabove, the risk determination module 156 may include a set ofinstructions stored in the memory 152 to cause the processor 150 todetermine if the driver exhibits aggressive driving behavior(s) byanalyzing the acceleration, braking, and/or number of times the vehicleexceeded the speed limit, etc. In another aspect, execution of the riskdetermination module 156 may cause the processor 150 to identify anaccident by processing data from the velocity subsystem 124 to identifya very sudden change in velocity of the electric vehicle 20, and/or byimplementing image/video processing of the data from external sensor 132to identify a collision with another vehicle and/or object, etc.

In one aspect, the processor 150 may execute the risk determinationmodule 156 to analyze the sensor data 154 substantially in real-time inorder to generate risk indicators reflecting the level of riskassociated with the environment in which the electric vehicle 20 isdriven, the operation of the electric vehicle 20, the condition of theelectric vehicle 20, the behavior of the driver of the electric vehicle20, and/or the behavior of the passengers of the electric vehicle 20.Once each risk indicator is generated for a particular time period, therisk indicator may be stored in the memory 152 as part of the risk data158, and the sensor data 154 that corresponds to that same time periodmay be erased to make room for new senor data. In this manner, thestorage requirements of the memory 152 may be reduced, which may beuseful in view of the large volume of data that may be generated by oneor more of the subsystems 122, 124, 126, 128, 130, the external sensor132, the cabin sensor 134, and/or other vehicle sensors and subsystems.As an alternative, in another aspect, the step of generating the riskdata 158 may be omitted from the method 300.

While the foregoing generally refers to the insurance risk related dataas being a separate item from the sensor data 154 and/or the risk data158, it should be understood that the insurance risk related data mayencompass the sensor data 154 and the risk data 158, as well as, othertypes of data.

Next, the method 300 may involve determining whether the electricvehicle 20 is connected to the electrical grid 12 for charging thebattery 110 of the electric vehicle 20 (block 320). In one aspect, thisstep may involve the vehicle control unit 149 receiving an indication(e.g., a signal) from the battery 110 that the battery 110 is beingcharged, an indication (e.g., a signal) from the power supply inlet 116that the power supply inlet 116 is electrically connected to theelectrical plug 118, an indication (e.g., a signal) from the power-linecommunication unit 170 that the power-line communication 170 isconfigured to transmit and/or receive information over the electricalgrid 12, and/or an indication (e.g., a signal) from the AC to DCconverter 120 that the AC to DC converter 120 is supplied withelectricity from the electrical grid 12. If the vehicle control unit 149determines that the electric vehicle 20 is not connected to theelectrical grid 12, the method 300 may return to block 305 to collectadditional insurance risk related data. On the other hand, if thevehicle control unit 149 determines that the electric vehicle 20 isconnected to the electrical grid 12, the method 300 may proceed to block325 to transmit the insurance risk related data over the electrical grid12.

In response to the indication that the electric vehicle 20 is connectedto the electrical grid 12, the processor 150 may execute a set ofinstructions stored in the power-line communication module 172 tocontrol the power-line communication unit 170 to transmit the insurancerisk related data over the electrical grid 12 to the computer system(s)of the insurer 16 and/or another remote entity (block 325). In oneaspect, prior to transmission, the electric vehicle 20 may receive arequest from the insurer 16, via the power-line communication unit 170,to transmit the insurance risk related data to the insurer 16. Theinsurer 16 may know that the electric vehicle 20 is capable of receivingsuch a request over the electrical grid 12 as the result of an electricutility company notifying the insurer 16 that the electric vehicle 20 isexerting a demand for power on the electrical grid 12.

In one aspect, a remote server operated by the insurer 16 mayperiodically check if the electric vehicle 20 is connected to theelectrical grid 12, at times when the electric vehicle 20 is expected tobe charging (e.g., every night at midnight, every day at 2:00 p.m.,etc.). The insurer 16 may check if the electric vehicle 20 is connectedto the electrical grid 12 by pinging an address where the electricvehicle 20 is customarily charged and/or by contacting an electricutility company to determine if they are aware of the electric vehicle20 being charged. Upon confirming that the electric vehicle 20 isconnected to the electrical grid 12 for charging, the insurer 16 maysend a request to the electric vehicle 20 over the electrical grid 12asking the electric vehicle 20 to transmit the insurance risk relateddata. The request may indicate a collection time frame for the insurancerisk related data to be transmitted (e.g., insurance risk related datacollected over the past day, week, month, etc.) and/or may indicate thatall insurance risk related data collected since the last transmissionshould be transmitted to the insurer 16. Reception of the request fromthe insurer 16 may cause the processor 150 of the electric vehicle 12 toexecute the power-line communication module 172, as discussed below, andtransmit the insurance risk related data with, or from, the power-linecommunication unit 170 over the electrical grid 12 to the insurer 16.

In one aspect, execution of the power-line communication module 172 maycause the processor 150 to transmit the sensor data 154, the risk data158, and/or other insurance risk related data stored in the memory 152to the power-line communication unit 170 and/or may cause the power-linecommunication unit 170 to retrieve the sensor data 154, the risk data158, and/or other insurance risk related data directly from the memory152.

Once in possession of the insurance risk related data, the power-linecommunication unit 170 may convert the insurance risk related data intoa modulated carrier signal (e.g., a radio frequency signal) that may betransmitted over the electrical grid 12 to the insurer 16. In oneaspect, where the power-line communication unit 170 is configured as aBPL modem, the power-line communication unit 170 may convert theinsurance risk related data into a modulated carrier signal having afrequency in the range of approximately (e.g., ± 10%) 1 to 100 MHz, or1.6 to 80 MHz, or 10 to 80 MHz, or 20 to 60 MHz, or lesser or greater.

The insurer 16 may receive the carrier signal representing the insurancerisk related data with the power-line communication unit 190 (block330). The power-line communication unit 190, which may be configured asa BPL modem, may convert the modulated carrier signal into digital datathat may be stored in the memory 194 of the data analysis unit 192 aspart of the collected vehicle data 196. Subsequently, the insurer 16 mayanalyze the collected vehicle data 196 by executing instructionsincluded in the risk determination module 200 and/or the insurancerating module 204 to generate risk indicators and/or insurance ratingdata (block 335). The risk determination module 200 and/or the insurancerating module 204 may operate in the manner discussed above to generatethe risk indicators and/or the insurance rating data. In one aspect, theinsurance rating data may correspond to the likelihood that the electricvehicle 20 and/or the driver of the electric vehicle 20 may be involvedin an accident causing damage or injury to the electric vehicle 20, thedriver of the electric vehicle 20, passengers of the electric vehicle20, other vehicles, other drivers and passengers, pedestrians, etc.Additionally, or as an alternative, the insurance rating data maycorrespond to a risk category for the electric vehicle 20 and/or thedriver of the electric vehicle 20 (e.g., high risk, moderate risk, lowrisk, etc.).

In one aspect, the insurance rating data may be provided to a billingunit (not illustrated) that is configured to determine premiums for aninsurance policy of the driver of the electric vehicle 20, or aninsurance policy associated with the electric vehicle 20, based upon theinsurance rating data (or, alternatively, based directly on the riskindicators), as discussed above. Also, the insurance rating data may ormay not include the insurance premium information.

After the insurance rating data has been calculated, the insurer 16 maytransmit the insurance rating data and/or other data (e.g.,advertisements, warning information, etc.) over the electrical grid 12to the electric vehicle 20 (block 340). This step may involve using thepower-line communication unit 190 to convert the insurance rating dataand/or other data into a modulated carrier signal having a frequency inthe range of approximately (e.g., ± 10%) 1 to 100 MHz, or 1.6 to 80 MHz,or 10 to 80 MHz, or 20 to 60 MHz, or lesser or greater. Subsequently,the power-line communication unit 170 of the electric vehicle mayreceive the modulated carrier signal and/or convert the modulatedcarrier signal into digital data that may be stored in the memory 152(block 345). Finally, in one aspect, the display of the 160 of the userinterface 159 may display the insurance rating data (e.g., the insurancepremium information calculated by the insurer 16) and/or other data tothe driver and/or other occupants of the electric vehicle 20.

The information which may be communicated to the vehicle 20 via thepower-line communication system is not limited to insurance rating data,and may be any type of information. In one aspect, a vehiclemanufacturer and/or the insurer 16 may communicate, via the power-linecommunication, warranty and/or recall information to the vehicle 20 fordisplay to the driver and/or software updates for updating the computersystems of the vehicle 20. Accordingly, the power-line communicationsystem of the present disclosure may be used to keep the driver aware ofthe latest safety information relevant to the vehicle 20 and/or providesupport for the software used by the vehicle 20.

VI. Exemplary Computer-Implemented Method

In one aspect, a computer-implemented method of communicating data withan electric vehicle may be provided. The method may include (a)collecting, at or via one or more vehicle-mounted processors, insurancerisk related data associated with use of the electric vehicle; (b)storing, at or via the one or more vehicle-mounted processors, theinsurance risk related data in one or more memories included in theelectric vehicle; (c) receiving, at or via the one or morevehicle-mounted processors, an indication that the electric vehicle isconnected to an electrical grid for charging a battery included in theelectric vehicle; and/or (d) transmitting, the insurance risk relateddata with, or from, a power-line communication unit, and/or under thedirection or control of the one or more vehicle-mounted processors, overthe electrical grid to one or more remote computer systems when theelectric vehicle is connected to the electrical grid for charging thebattery to facilitate insurance product pricing that is more reflectiveof actual risk. The insurance risk related data may include odometerinformation, steering information, acceleration information, brakinginformation, velocity information, engine performance information,vehicle maintenance information, proximity information, driftinginformation, lane changing information, weather information, driverbehavior information, passenger information, and/or geographic locationinformation. The insurance risk related data may be collected from oneor more sensors included in the electric vehicle. Also, the power-linecommunication unit may be a broadband over power line (BPL) modem. Themethod may include additional, fewer, or alternate actions, includingthose discussed elsewhere herein.

The method discussed above and herein may further include determining,with the one or more remote computer systems, insurance rating databased upon the insurance risk related data. Additionally, the method mayinclude receiving, with or via the power-line communication unit and/orthe one or more vehicle-mounted processors, insurance rating datatransmitted over the electrical grid from the one or more remotecomputer systems. In one aspect, the method includes displaying, to adriver of the electric vehicle, a notification based upon the insurancerating data.

The method discussed above and herein may include, prior to transmittingthe insurance risk related data, receiving, with the power-linecommunication unit, a request to transmit the insurance risk relateddata transmitted over the electrical grid to an insurance provider.

VII. Additional Considerations

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Certain implementations are described herein as including logic or anumber of components, modules, or mechanisms. Modules may constituteeither software modules (e.g., code implemented on a tangible,non-transitory machine-readable medium such as RAM, ROM, flash memory ofa computer, hard disk drive, optical disk drive, tape drive, etc.) orhardware modules (e.g., an integrated circuit, an application-specificintegrated circuit (ASIC), a field programmable logic array (FPLA) /field-programmable gate array (FPGA), etc.). A hardware module is atangible unit capable of performing certain operations and may beconfigured or arranged in a certain manner. In exemplaryimplementations, one or more computer systems (e.g., a standalone,client or server computer system) or one or more hardware modules of acomputer system (e.g., a processor or a group of processors) may beconfigured by software (e.g., an application or application portion) asa hardware module that operates to perform certain operations asdescribed herein.

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“presenting,” “displaying,” or the like may refer to actions orprocesses of a machine (e.g., a computer) that manipulates or transformsdata represented as physical (e.g., electronic, magnetic, or optical)quantities within one or more memories (e.g., volatile memory,non-volatile memory, or a combination thereof), registers, or othermachine components that receive, store, transmit, or displayinformation.

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus.

In addition, use of the “a” or “an” are employed to describe elementsand components of the implementations herein. This is done merely forconvenience and to give a general sense of the invention. Thisdescription should be read to include one or at least one and thesingular also includes the plural unless it is obvious that it is meantotherwise.

Upon reading this disclosure, those of skill in the art will appreciatestill additional alternative structural and functional designs for asystem and a method for communication data with an electric vehiclethrough the disclosed principles herein. Thus, while particularimplementations and applications have been illustrated and described, itis to be understood that the disclosed implementations are not limitedto the precise construction and components disclosed herein. Variousmodifications, changes and variations, which will be apparent to thoseskilled in the art, may be made in the arrangement, operation anddetails of the method and apparatus disclosed herein without departingfrom the spirit and scope defined in the appended claims.

Although the foregoing text sets forth a detailed description ofnumerous different implementations, it should be understood that thelegal scope of the invention is defined by the words of the claims setforth at the end of this patent. The detailed description is to beconstrued as exemplary only and does not describe every possibleimplementation, as describing every possible implementation would beimpractical, if not impossible. One could implement numerous alternateconfigurations, using either current technology or technology developedafter the filing date of this patent, which would still fall within thescope of the claims.

What is claimed is:
 1. A computer-implemented method of communicatingdata with an electric vehicle, the method comprising: collecting, at orvia one or more vehicle-mounted processors, insurance risk related dataassociated with use of the electric vehicle; storing the insurance riskrelated data in one or more memories included in the electric vehicle;determining, at or via the one or more vehicle-mounted processors, thatthe electric vehicle is connected to an electrical grid for charging abattery included in the electric vehicle; and transmitting, theinsurance risk related data with, or from, a power-line communicationunit, and/or under the direction or control of the one or morevehicle-mounted processors, over the electrical grid to one or moreremote computer systems when the electric vehicle is connected to theelectrical grid for charging the battery to facilitate insurance productpricing that is more reflective of actual risk, wherein the transmissionof insurance risk related data is triggered or caused by, or conditionedupon, at least in part, the determination that the electric vehicle isconnected to the electrical grid for charging the battery.
 2. The methodof claim 1, the insurance risk related data including at least one of:odometer information, steering information, acceleration information,braking information, velocity information, engine performanceinformation, vehicle maintenance information, proximity information,drifting information, lane changing information, weather information,driver behavior information, passenger information, or geographiclocation information.
 3. The method of claim 1, comprising determining,with the one or more remote computer systems, insurance rating databased upon the insurance risk related data.
 4. The method of claim 1,comprising receiving, with or via the power-line communication unitand/or the one or more vehicle-mounted processors, insurance rating datatransmitted over the electrical grid from the one or more remotecomputer systems.
 5. The method of claim 4, comprising displaying, to adriver of the electric vehicle, a notification based upon the insurancerating data.
 6. The method of claim 1, comprising receiving, with thepower-line communication unit, a request to transmit the insurance riskrelated data transmitted over the electrical grid to an insuranceprovider.
 7. The method of claim 1, collecting the insurance riskrelated data from one or more sensors included in the electric vehicle.8. The method of claim 1, the power-line communication unit being abroadband over power line (BPL) modem.
 9. The method of claim 1,comprising receiving, with the power-line communication unit, a requestto transmit the one or more risk indicators over the electrical grid,wherein the request is limited to one or more risk indicators generatedby the one or more vehicle-mounted processors after a previoustransmission of one or more risk indicators by the electric vehicle overthe electrical grid.
 10. A system of communicating data with an electricvehicle, the system comprising: one or more processors; and one or morememories connected to the one or more processors, the one or morememories including non-transitory computer-readable instructions that,when executed by the one or more processors, cause the one or moreprocessors to: collect insurance risk related data associated with useof the electric vehicle; store the insurance risk related data in theone or more memories; determine that the electric vehicle is connectedto an electrical grid for charging a battery included in the electricvehicle; and control a power-line communication unit to transmit theinsurance risk related data over the electrical grid to one or moreremote computer systems, wherein the transmission of insurance riskrelated data is triggered or caused by, or conditioned upon, at least inpart the determination that the electric vehicle is connected to theelectrical grid for charging the battery.
 11. The data communicationsystem of claim 10, the insurance risk related data including at leastone of: odometer information, steering information, accelerationinformation, braking information, velocity information, engineperformance information, vehicle maintenance information, proximityinformation, drifting information, lane changing information, weatherinformation, driver behavior information, passenger information, orgeographic location information.
 12. The data communication system ofclaim 10, wherein the non-transitory computer-readable instructionsinclude instructions that cause the one or more processors to control apower-line communication unit to receive insurance rating datatransmitted over the electrical grid from the one or more remotecomputer systems.
 13. The data communication system of claim 12, whereinthe insurance rating data is determined based upon the insurance riskrelated data.
 14. The data communication system of claim 10, thepower-line communication unit being included in a charging unit separatefrom the electric vehicle.
 15. The data communication system of claim10, wherein the non-transitory computer-readable instructions includeinstructions that cause the one or more processors to collect theinsurance risk related data from one or more sensors included in theelectric vehicle.
 16. The data communication system of claim 10, thepower-line communication unit being a broadband over power line (BPL)modem.
 17. A tangible computer-readable medium including non-transitorycomputer-readable instructions that, when executed at one or moreprocessors of a communication system for an electric vehicle, cause theone or more processors to: collect insurance risk related dataassociated with use of the electric vehicle; store the insurance riskrelated data in one or more memories included in the electric vehicle;determine that the electric vehicle is connected to an electrical gridfor charging a battery included in the electric vehicle; and transmitthe insurance risk related data with a power-line communication unitover the electrical grid to one or more remote computer systems when theelectric vehicle is connected to the electrical grid for charging thebattery, wherein the transmission of insurance risk related data istriggered or caused by, or conditioned upon, at least in part, thedetermination that the electric vehicle is connected to the electricalgrid for charging the battery.
 18. The tangible computer-readable mediumof claim 17, the insurance risk related data including at least one of:odometer information, steering information, acceleration information,braking information, velocity information, engine performanceinformation, vehicle maintenance information, proximity information,drifting information, lane changing information, weather information,driver behavior information, passenger information, or geographiclocation information.
 19. The tangible computer-readable medium of claim17, wherein the non-transitory computer-readable instructions includeinstructions that cause the one or more processors to control apower-line communication unit to receive insurance rating datatransmitted over the electrical grid from the one or more remotecomputer systems.
 20. The tangible computer-readable medium of claim 19,wherein the insurance rating data is determined based upon the insurancerisk related data.
 21. The tangible computer-readable medium of claim17, wherein the non-transitory computer-readable instructions includeinstructions that cause the one or more processors to collect theinsurance risk related data from one or more sensors included in theelectric vehicle.